CSC 400-1
Michael Scott
F 9:00AM - 10:15AM
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An introduction to the technical, social, economic, and political aspects of graduate education in computer science at Rochester. Class meetings consist primarily of group discussions and presentations that focus on a broad range of topics, and are intended to improve the critical analysis, technical writing, presentation, and problem-solving skills of students. Both class discussions and written assignments are drawn from material presented in other first-year graduate courses offered within the department. The course also offers a forum for individual department faculty members to discuss their research interests and recent results. Satisfactory performance is required of all first-year graduate students.
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CSC 404-1
Michael Huang
WF 3:25PM - 4:40PM
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This course provides in-depth discussions of the design and implementation issues of multiprocessor system architecture. Topics include cache coherence, memory consistency, interconnect, their interplay and impact on the design of high-performance micro-architectures. prerequisite ECE 200 or CSC 252 or permission of instructor
- Location
- Computer Studies Room 601
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CSC 412-1
Ehsan Hoque
TR 12:30PM - 1:45PM
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This course will explore the design, implementation, and evaluation of user interfaces. Students will study the theoretical methods for interface design and evaluation, including requirements gathering, usability heuristics, user interface inspections, usability studies, information visualization, and prototyping. Case studies of interface successes and failures will augment theory with practical experiences. Students will apply this methodology to assignments in the design, implementation, and evaluation cycle. Students taking this course at the graduate level will have additional readings and assignments.
- Location
- Meliora Room 203
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CSC 414-1
Mujdat Cetin
MW 10:25AM - 11:40AM
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This is the second course offered as part of the PhD training program on augmented and virtual reality. It builds on the first course, Introduction to Augmented and Virtual Reality (AR/VR). The goal of the course is to provide exposure to problems in the AR/VR domain addressed by various disciplines. The course consists of three one-month long modules in a semester. Modules engage students in particular aspects of AR/VR or hands-on experience on AR/VR. Modules to be offered in various years include: fundamentals of optics for AR/VR; AR/VR in the silicon; foundations of visual perception in the context of AR/VR; computer audition and acoustic rendering; measuring the human brain; deep learning and visual recognition for AR/VR; brain-computer interfacing in a virtual environment; 3D interfaces and interaction; AR/VR for collaborative education & professional training. In Spring 2021, the following three modules will be offered: 1) AR/VR in the silicon (Prof. Yuhao Zhu). This module will first take a look at how AR and VR are evolving and some applications and use cases. Then, we will provide a review of some of the key technology challenges in silicon, a.k.a., processor chips, that need to be overcome before widespread deployment of AR and VR and the breakthroughs in silicon that are required to enable this future. We will then discuss some recent advances proposed to meet the silicon performance/power targets. 2) Brain-computer interfacing in a virtual environment (Prof. Mujdat Cetin). Brain-computer interface (BCI) systems aim to establish direct interaction channels between the brain and external devices. In this module, we will explore recent and ongoing efforts to couple noninvasive EEG-based BCIs with AR/VR systems. The module will cover topics including (1) brain activity as a control signal in AR/VR systems, (2) cognitive state monitoring and affective BCIs in virtual environments, (3) analyzing neural activity to guide AR/VR system design. 3) Professional encounters with leading AR/VR researchers. This module will involve a series of seminars and discussion sessions with leading AR/VR researchers from academia and industry. prerequisites: ECE 410 or OPT 410 or BME 410 or NSCI 415 or CSC 413 or CVSC 534
- Location
- Online Room 17 (ASE)
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CSC 440-1
Thaddeus Pawlicki
TR 4:50PM - 6:05PM
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Fundamental concepts and techniques of data mining, including data attributes, data visualization, data pre-processing, mining frequent patterns, association and correlation, classification methods, and cluster analysis. Advanced topics include outlier detection, stream mining, and social media data mining. CSC 440, a graduate-level course, requires additional readings and a course project.
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- Online Room 4 (ASE)
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CSC 443-1
Ralf Haefner
F 2:00PM - 3:15PM
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This is a rotating topics course that includes the study of both the computations performed by the brain and of computational models of neuronal responses. Primary focus will be on the visual system. This course is taught at an introductory level in odd numbered years and an advanced level in even numbered years. Programming experience is required.
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- Computer Studies Room 209
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CSC 443-3
Ralf Haefner
MW 2:00PM - 3:15PM
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This course is cross-listed with BCS 547. Please refer to that course description.
- Location
- Online Room 27 (ASE)
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CSC 446-1
Daniel Gildea
TR 11:05AM - 12:20PM
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This course presents the mathematical foundations of AI, including probability, decision theory and machine learning. Prerequisites: MATH 164 and MATH 165
- Location
- Online Room 3 (ASE)
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CSC 447-1
James Allen
MW 12:30PM - 1:45PM
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This course addresses issues of representing computing meaning from natural language, especially issues of understanding language in context using commonsense knowledge of the world. Topics will include a survey of English phrase structure and parsing, semantic representation (e.g., events, semantic roles, time, causality and speech acts), and theories and techniques for understanding language in context, including intention recognition, text understanding using knowledge of scripts and plans, and models of spoken dialogue systems (e.g., conversational agents such as Siri). CSC447, the graduate level version of the course, requires a substantial individual project.Prerequisites: CSC 242
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- Online Room 17 (ASE)
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CSC 449-1
Jiebo Luo
TR 12:30PM - 1:45PM
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Introduction to computer vision, including camera models, basic image processing, pattern and object recognition, and elements of human vision. Specific topics include geometric issues, statistical models, Hough transforms, color theory, texture, and optic flow. CSC 449, a graduate-level course, requires additional readings and assignments.Prerequisites: MATH 161 and CSC 242; MATH 165 strongly recommended
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- Harkness Room 115
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CSC 452-1
Yuhao Zhu
TR 12:30PM - 1:45PM
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Introduction to computer architecture and the layering of hardware/software systems. Topics include instruction set design; logical building blocks; computer arithmetic; processor organization; the memory hierarchy (registers, caches, main memory, and secondary storage); I/Obuses, devices, and interrupts; microcode and assembly language; virtual machines; the roles of the assembler, linker, compiler, and operating system; technological trends and the future of computing hardware. Several programming assignments required.
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- Online Room 16 (ASE)
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CSC 455-1
Sreepathi Pai
MW 10:25AM - 11:40AM
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Programming is the automation of information processing. Program analysis and transformation is the automation of programming itself---how much a program can understand and improve other programs. Because of the diversity and complexity of computer hardware, programmers increasingly depend on automation in compilers and other tools to deliver efficient and reliable software. This course combines fundamental principles and (hands-on) practical applications. Specific topics include data flow and dependence theories; static and dynamic program transformation including parallelization; memory and cache management; type checking and program verification; and performance analysis and modeling. The knowledge and practice will help students to become experts in software performance and correctness. Students taking the graduate level will have additional course requirements and a more difficult project.
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- Bausch & Lomb Room 106
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CSC 458-1
Sandhya Dwarkadas
MW 3:25PM - 4:40PM
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Principles of parallel and distributed systems, and the associated implementation and performance issues. Topics covered will include programming interfaces to parallel and distributed computing, interprocess communication, synchronization, and consistency models, fault tolerance and reliability, distributed process management, distributed file systems, multiprocessor architectures, parallel program optimization, and parallelizing compilers. Students taking this course at the 400 level will be required to complete additional readings and/or assignments.
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- Online Room 19 (ASE)
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CSC 461-1
Eustrat Zhupa
MW 3:25PM - 4:40PM
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This course presents the fundamental concepts of database design and use. It provides a study of data models, data description languages, and query facilities including relational algebra and SQL, data normalization, transactions and their properties, physical data organization and indexing, security issues and object databases. It also looks at the new trends in databases. The knowledge of the above topics will be applied in the design and implementation of a database application using a target database management system as part of a semester-long group project.
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- Online Room 5 (ASE)
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CSC 463-1
Fatemeh Nargesian
TR 2:00PM - 3:15PM
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This course explores the internals of data engines. Topics covered will include the relational model; relational database design principles based on dependencies and normal forms; query execution; transactions; recovery; query optimization; parallel query processing; NoSQL.
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- Online Room 23 (ASE)
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CSC 465-1
Yusuf Bilgic
TR 4:50PM - 6:05PM
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This course is a continuation of DSCC/CSC 462, covering intermediate statistical methodology and related computational methods, with an emphasis on the R statistical computing environment. PREREQUISITE: DSCC/CSC/TCSC 262 or instructor permission of equivalent coursework
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- Online Room 3 (ASE)
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CSC 478-1
John Criswell
MW 6:15PM - 7:30PM
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This course will teach students the foundations of computer security. Students will learn what security is, the design principles of secure systems, how security is enforced, and how security is compromised. Topics include access controls, information flow, basic applications of cryptography, buffer overflow attacks, and malware.
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- Online Room 24 (ASE)
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CSC 480-1
Lane Hemaspaandra
MW 3:25PM - 4:40PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Prerequisites: CSC 173 and MTH 150. YOU MUST REGISTER FOR A RECITATION WHENREGISTERING FOR THE MAIN COURSE
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- Online Room 24 (ASE)
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CSC 480-10
Lane Hemaspaandra
W 4:50PM - 6:05PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
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- Online Room 1 (ASE)
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CSC 480-2
Lane Hemaspaandra
W 4:50PM - 6:05PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
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- Online Room 3 (ASE)
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CSC 480-3
Lane Hemaspaandra
W 6:15PM - 7:30PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
- Location
- Online Room 1 (ASE)
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CSC 480-4
Lane Hemaspaandra
R 4:50PM - 6:05PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
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- Online Room 6 (ASE)
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CSC 480-5
Lane Hemaspaandra
R 6:15PM - 7:30PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
- Location
- Online Room 3 (ASE)
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CSC 480-6
Lane Hemaspaandra
R 7:40PM - 8:55PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
- Location
- Online Room 27 (ASE)
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CSC 480-7
Lane Hemaspaandra
W 6:15PM - 7:30PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
- Location
- Online Room 2 (ASE)
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CSC 480-8
Lane Hemaspaandra
R 4:40PM - 6:05PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
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- Online Room 7 (ASE)
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CSC 480-9
Lane Hemaspaandra
R 3:25PM - 4:40PM
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This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.
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- Online Room 26 (ASE)
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CSC 481-1
Muthuramakrishnan Venkitasubramaniam
TR 2:00PM - 3:15PM
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The modern study of cryptography investigates techniques for facilitating interactions between distrustful entities. In this course we introduce some of the fundamental concepts of this study. Emphasis will be placed on the foundations of cryptography and in particular on precise definitions and proof techniques.(MTH 150 or MTH 162), AND (CSC 171 or prior programming experience)
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- Online Room 7 (ASE)
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CSC 481-2
Muthuramakrishnan Venkitasubramaniam
W 6:15PM - 7:30PM
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Please refer to CSC281 for course description.
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- Online Room 7 (ASE)
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CSC 482-1
Eustrat Zhupa
TR 3:25PM - 4:40PM
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How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems.Prerequisites: (CSC 172 and MTH 150) or MTH172.
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- Online Room 24 (ASE)
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CSC 482-2
Eustrat Zhupa
T 6:15PM - 7:30PM
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How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems.
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- Online Room 10 (ASE)
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CSC 482-3
Eustrat Zhupa
W 6:15PM - 7:30PM
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How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems.
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- Online Room 21 (ASE)
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CSC 482-4
Eustrat Zhupa
M 6:15PM - 7:30PM
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How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems.
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- Online Room 20 (ASE)
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CSC 482-5
Eustrat Zhupa
W 7:40PM - 8:55PM
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How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems.
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- Online Room 1 (ASE)
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CSC 486-1
Lane Hemaspaandra
MW 2:00PM - 3:15PM
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The difference between computable and uncomputable problems and between feasible and infeasible problems. Regarding the latter, what properties of a problem make it computationally simple? What properties of a problem may preclude its having efficient algorithms? How computationally hard are problems? Complete sets and low information content; P=NP?; unambiguous computation and one-way functions; reductions relating the complexity of problems; complexity classes and hierarchies. Prerequisites: CSC 280
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- Online Room 7 (ASE)
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CSC 495-01
James Allen
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CSC 495-02
John Criswell
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CSC 495-03
Zhen Bai
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CSC 495-04
Chen Ding
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CSC 495-05
Sandhya Dwarkadas
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CSC 495-06
Daniel Gildea
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CSC 495-07
Lane Hemaspaandra
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CSC 495-08
Ehsan Hoque
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CSC 495-09
Henry Kautz
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CSC 495-10
Jiebo Luo
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CSC 495-11
Fatemeh Nargesian
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CSC 495-12
Randal Nelson (Terminated)
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CSC 495-13
Sreepathi Pai
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CSC 495-14
Lenhart Schubert
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CSC 495-15
Michael Scott
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CSC 495-16
Daniel Stefankovic
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CSC 495-17
Muthuramakrishnan Venkitasubramaniam
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CSC 495-18
Chenliang Xu
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CSC 495-19
Yuhao Zhu
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CSC 531-1
Ehsan Hoque
F 11:00AM - 12:30PM
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The course is required for students supported by the BCS/CS NRT graduate training grant, and should be taken the semester after the corresponding course DSCC/BCSC/CSC 530. Research Seminars 11:00am-12:30pm on Friday 2/12, 3/12 & 4/9. Communication Workshops 5-7pm on Tuesday 2/2, 3/9 & 4/6.
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- Online Room 29 (ASE)
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CSC 577-1
Chenliang Xu
TR 9:40AM - 10:55AM
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This is a seminar course with varying topics in the area of artificial Intelligence. May not be taught every year. This course covers advanced research topics in computer vision with an emphasis on learning structured representations and embeddings. Approaches for learning from unimodal (e.g., images and videos), and multimodal data (e.g., vision and language, vision and audio) will be covered and include topics from structured predications, deep learning and others. The course will be a mix of lecture, student presentation and discussion.
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- Online Room 17 (ASE)
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CSC 595--02
John Criswell
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CSC 595-01
James Allen
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CSC 595-03
Zhen Bai
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CSC 595-04
Chen Ding
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CSC 595-05
Sandhya Dwarkadas
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CSC 595-06
Daniel Gildea
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CSC 595-07
Lane Hemaspaandra
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CSC 595-08
Ehsan Hoque
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CSC 595-09
Henry Kautz
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CSC 595-10
Jiebo Luo
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CSC 595-11
Fatemeh Nargesian
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CSC 595-12
Ji Liu
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CSC 595-13
Sreepathi Pai
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CSC 595-14
Lenhart Schubert
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CSC 595-15
Michael Scott
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CSC 595-16
Daniel Stefankovic
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CSC 595-17
Muthuramakrishnan Venkitasubramaniam
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CSC 595-18
Chenliang Xu
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CSC 595-19
Yuhao Zhu
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CSC 595-20
Aaron White
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CSC 595-21
Gonzalo Mateos Buckstein
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CSC 595-22
Thomas Howard
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CSC 895-1
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CSC 897-02
Sandhya Dwarkadas
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CSC 897-03
Daniel Gildea
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CSC 897-04
Chen Ding
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CSC 897-05
John Criswell
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CSC 897-06
Muthuramakrishnan Venkitasubramaniam
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CSC 897-07
Lenhart Schubert
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CSC 897-08
Zhen Bai
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CSC 897-09
Chenliang Xu
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CSC 897-1
Michael Scott
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CSC 897-10
Sreepathi Pai
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CSC 897-11
Daniel Stefankovic
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CSC 897-12
James Allen
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CSC 897-13
Yuhao Zhu
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CSC 897-14
Jiebo Luo
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CSC 897-15
Ehsan Hoque
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CSC 897-16
Henry Kautz
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CSC 899-01
James Allen
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CSC 899-02
John Criswell
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CSC 899-03
Zhen Bai
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CSC 899-04
Sandhya Dwarkadas
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CSC 899-05
Chen Ding
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CSC 899-06
Daniel Gildea
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CSC 899-07
Lane Hemaspaandra
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CSC 899-08
Ehsan Hoque
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CSC 899-09
Henry Kautz
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CSC 899-10
Jiebo Luo
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CSC 899-11
Fatemeh Nargesian
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CSC 899-12
Randal Nelson (Terminated)
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CSC 899-13
Sreepathi Pai
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CSC 899-14
Lenhart Schubert
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CSC 899-15
Michael Scott
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CSC 899-16
Daniel Stefankovic
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CSC 899-17
Muthuramakrishnan Venkitasubramaniam
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CSC 899-18
Chenliang Xu
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CSC 899-19
Yuhao Zhu
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CSC 995-1
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CSC 997-02
Sandhya Dwarkadas
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CSC 997-03
Daniel Gildea
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CSC 997-04
Chen Ding
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CSC 997-05
John Criswell
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CSC 997-06
Muthuramakrishnan Venkitasubramaniam
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CSC 997-07
Lenhart Schubert
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CSC 997-08
Zhen Bai
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CSC 997-09
Chenliang Xu
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CSC 997-1
Michael Scott
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CSC 997-10
Sreepathi Pai
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CSC 997-11
Daniel Stefankovic
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CSC 997-12
James Allen
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CSC 997-13
Yuhao Zhu
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CSC 997-14
Jiebo Luo
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CSC 997-15
Ehsan Hoque
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CSC 997-16
Henry Kautz
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CSC 997B-1
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CSC 999-01
James Allen
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CSC 999-02
John Criswell
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CSC 999-03
Zhen Bai
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CSC 999-04
Chen Ding
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CSC 999-05
Sandhya Dwarkadas
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CSC 999-06
Daniel Gildea
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CSC 999-07
Lane Hemaspaandra
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CSC 999-08
Ehsan Hoque
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CSC 999-09
Henry Kautz
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CSC 999-10
Jiebo Luo
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CSC 999-11
Fatemeh Nargesian
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CSC 999-12
Ji Liu
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CSC 999-13
Sreepathi Pai
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CSC 999-14
Lenhart Schubert
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CSC 999-15
Michael Scott
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CSC 999-16
Daniel Stefankovic
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CSC 999-17
Muthuramakrishnan Venkitasubramaniam
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CSC 999-18
Chenliang Xu
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CSC 999-19
Yuhao Zhu
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CSC 999-20
Aaron White
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CSC 999-21
Gonzalo Mateos Buckstein
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CSC 999-22
Thomas Howard
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